摘要
为了有效保证物流仓储环境下AGV运行的高安全、低能耗等目标,设计了一种基于改进蚁群算法的AGV多目标路径规划算法。首先,基于物流仓储环境对AGV作业需求综合分析,选取路径长度、转角和、危险率和避障等待时间等因素作为路径规划的子目标,并采用熵权法确定各子目标的权值,建立AGV多目标规划模型;其次,改进蚁群下一栅格选取方式避免顶点碰撞,并在蚁群算法中引入非支配排序算法改进信息素给予机制,使蚁群寻路时受多个子目标共同引导,将蚁群算法扩展到多个目标函数优化。仿真结果表明,所设计算法实现了AGV合理、安全、有效的多目标路径规划。
In order to effectively ensure the high safety and low energy consumption of AGV operation in logistics and storage environment,a multi-objective AGV path planning algorithm based on improved ant colony algorithm was designed.First of all,based on the comprehensive analysis of AGV operation demand in logistics and warehousing environment,factors such as path length,corner sum,risk rate and the wait time of obstacle avoidance are selected as the sub-goals of path planning.Entropy weight method is adopted to determine the weights of each sub-target,and AGV multi-objective planning model is established.Then,the next grid selection method of ant colony is improved to avoid vertex collisions,and the pheromone giving mechanism of non-dominant sorting algorithm is introduced into the ant colony algorithm,so that the ant colony pathfinding is guided by multiple sub-targets,and the ant colony algorithm is extended to multiple objective function optimization.The simulation results show that the proposed algorithm can realize AGV multi-objective path planning reasonably,safely and effectively.
作者
李传奇
黄卫华
章政
金震
张子然
LI Chuan-qi;HUANG Wei-hua;ZHANG Zheng;JIN Zhen;ZHANG Zi-ran(Institute of Robotics and Intelligent Systems,Wuhan University of Science and Technology,Wuhan Hubei 430081,China;Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education,Wuhan University of Science and Technology,Wuhan Hubei 430081,China;School of Information Science and Engineering,Wuhan University of Science and Technology,Wuhan Hubei 430081,China)
出处
《组合机床与自动化加工技术》
北大核心
2021年第10期1-5,共5页
Modular Machine Tool & Automatic Manufacturing Technique
基金
国家自然科学基金(61773298)
冶金自动化与检测技术教育部工程研究中心开放基金资助项目(MADT201603)
2017年度武汉科技大学国防预研基金项目(GF201706)。
关键词
AGV
路径规划
多目标
蚁群算法
AGV
path planning
multi-objective
ant colony algorithm
